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check_scenario_node_payload

Read-only

Dry-run a scenario node 'payload' against its config class BEFORE writing it: reports unknown/misspelled properties and type mismatches, and returns the normalized JSON. Read-only — nothing is created or changed. Worth calling for any node type whose get_scenario_node_schema card says validation=NONE, because there the server accepts a broken payload silently and the node only misbehaves once a contact reaches it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payloadYesThe payload JSON you intend to send, as a string.
actionTypeYesNode type (C# class name), e.g. 'SendEmailScenarioAction'.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint annotation, the description adds meaningful behavioral detail: nothing is created or changed, it reports unknown/misspelled properties and type mismatches, it returns normalized JSON, and it warns that the server silently accepts broken payloads when validation=NONE. This gives the agent a realistic model of the tool's behavior without contradicting any annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences with no fluff: the first sentence states the action and results, the second states safety, and the third gives concrete usage guidance. The most important information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity tool with two simple parameters, present annotations, and no output schema, the description covers purpose, behavior, return value, and usage context. An agent has enough to decide whether and how to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes both parameters clearly and completely (payload string and actionType string), so the baseline is 3. The description ties the parameters to the tool's purpose, calling payload 'the payload JSON you intend to send' and actionType 'Node type (C# class name)', but does not add substantially beyond the schema's descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb, 'Dry-run', and clearly identifies the resource: a scenario node payload checked against its config class before writing. It also distinguishes itself from siblings by stating exactly what it reports and what it returns, so an agent can tell it apart from schema and operation tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit guidance on when to call the tool: before writing a payload, especially for nodes whose get_scenario_node_schema card says validation=NONE. It explains the consequence of not calling it in that situation, though it does not explicitly state when not to use it or name an alternative tool for validation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0
Disambiguation5/5

Every tool has a clearly scoped target: discovery, schema introspection, validation, execution, docs, and image services are all distinct. Closely related tools like list_modules/list_operations/search_operations and get_scenario_node_schema/check_scenario_node_payload are explicitly differentiated by their descriptions.

Naming Consistency4/5

Almost all tools follow a predictable verb_noun snake_case pattern such as get_*, list_*, search_*, generate_*, and import_*. The lone noun-style capability_map and the unique check_ verb are minor deviations rather than a broken convention.

Tool Count4/5

16 tools is slightly above the ideal 3–15 range, but the count is justified by the broad Admin API surface covering discovery, schemas, validation, execution, recipes, docs, and images. It is dense but not bloated.

Completeness5/5

The set covers the full discovery–schema–recipe–execute lifecycle, plus validation for opaque polymorphic types and product documentation lookup. invoke_operation delegates to the entire Admin API, so there are no dead ends; any arguable gaps are reachable through that operation.

Resources